Objective: There are limited data on the use of the creation tuberculin skin test (C-TST) for detecting tuberculosis (TB) infection (TBI) in individuals under 18 years of age. We conducted a study to assess the diagnostic accuracy of C-TST in this population.

Methods: A double-blind, randomized controlled trial was conducted across 4 tertiary hospitals in China to evaluate the diagnostic accuracy of the C-TST in detecting TBI in individuals under 18 years of age. Participants with suspected pulmonary TB, extrapulmonary TB, or non-TB pulmonary disease were enrolled. The primary outcome was the diagnostic accuracy of the C-TST. Secondary outcomes included the consistency among C-TST, the traditional tuberculin skin test (TST), and T-SPOT.TB assays in different subgroups, as well as the safety of C-TST. Each participant underwent all 3 tests simultaneously: T-SPOT.TB assay, TST, and C-TST.

Results: C-TST showed a sensitivity of 83.0 % (95 % CI, 68.7 %–91.9 %), while TST and T-SPOT.TB demonstrated sensitivities of 80.9 % (95 % CI, 66.3 %–90.4 %) and 76.6 % (95 % CI, 61.6 %–87.2 %), respectively. The specificities of C-TST, TST, and T-SPOT.TB were 100 % (95 % CI, 91.9 %–100 %), 98.0 % (95 % CI, 87.8 %–99.9 %), and 100 % (95 % CI, 90.9 %–100 %), respectively. The consistency between C-TST and T-SPOT.TB was high (kappa = 0.847). No serious adverse events (AEs) were reported.

Conclusions: This study demonstrates that C-TST is a reliable and safe diagnostic tool for detecting TBI in children and adolescents. It shows higher sensitivity than both T-SPOT.TB and the traditional TST, with no associated serious AEs. Therefore, C-TST is an effective and safe option for diagnosing TBI in this age group.

Identifying embryos with the highest likelihood of successful implantation is a critical component of the in vitro fertilization (IVF) process. Visual assessments are limited by the subjectivity of embryologists, making consistent evaluation of embryo health challenging with traditional methods. Recent advances in artificial intelligence (AI)—particularly in computer vision and deep learning—have enabled the automated analysis of embryo morphology images, reducing subjectivity and improving evaluation efficiency. Through an extensive literature search using keywords such as “embryo health assessment” and “artificial intelligence,” the present review focuses on AI-driven approaches for automated embryo evaluation. It examines AI techniques applied to embryo assessment across the early development, blastocyst, and full developmental stages. This review indicated the promising potential of AI technologies in enhancing the precision, consistency, and speed of embryo selection. AI models have been reported to outperform manual evaluations across several parameters, offering promising opportunities to improve success rates and operational efficiency in reproductive medicine. Additionally, this review discusses the current limitations of AI implementation in clinical settings and explores future research directions. Overall, the review provides insight into AI’s growing role in advancing embryo selection and highlights the path toward fully automated evaluation systems in assisted reproductive technology. 

Neuromorphic devices have shown great potential in simulating the function of biological neurons due to their efficient parallel information processing and low energy consumption. MXene-Ti₃C₂T_x, an emerging two-dimensional material, stands out as an ideal candidate for fabricating neuromorphic devices. Its exceptional electrical performance and robust mechanical properties make it an ideal choice for this purpose. This review aims to uncover the advantages and properties of MXene-Ti₃C₂T_x in neuromorphic devices and to promote its further development. Firstly, we categorize several core physical mechanisms present in MXene-Ti₃C₂T_x neuromorphic devices and summarize in detail the reasons for their formation. Then, this work systematically summarizes and classifies advanced techniques for the three main optimization pathways of MXene-Ti₃C₂T_x, such as doping engineering, interface engineering, and structural engineering. Significantly, this work highlights innovative applications of MXene-Ti₃C₂T_x neuromorphic devices in cutting-edge computing paradigms, particularly near-sensor computing and in-sensor computing. Finally, this review carefully compiles a table that integrates almost all research results involving MXene-Ti₃C₂T_x neuromorphic devices and discusses the challenges, development prospects, and feasibility of MXene-Ti₃C₂T_x-based neuromorphic devices in practical applications, aiming to lay a solid theoretical foundation and provide technical support for further exploration and application of MXene-Ti₃C₂T_x in the field of neuromorphic devices.

Currently, perovskite solar cells have achieved commendable progresses in power conversion efficiency (PCE) and operational stability. However, some conventional laboratory-scale fabrication methods become challenging when scaling up material syntheses or device production. Particularly, the prolonged high-temperature annealing process for the crystallization of perovskites requires a substantial amount of energy consumption and impact the modules’ throughput. Here, we report a modified near-infrared annealing (NIRA) process, which involves the excess PbI₂ engineered crystallization, efficiently reduces the preparation time for perovskite active layer to within 20 s compared to dozens of min in conventional hot plate annealing (HPA) process. The study showed that the incorporated PbI₂ promoted the consistent nucleation of the perovskite film, leading to the subsequent rapid and homogeneous crystallization at the NIRA stage. Thus, highly crystalized perovskite film was realized with even better crystallization performance than conventional HPA-based film. Ultimately, efficient perovskite solar modules of 36 and 100 cm² were readily fabricated with the optimal PCEs of 22.03% and 20.18%, respectively. This study demonstrates, for the first time, the successful achievement of homogeneous and high-quality crystallization in large-area perovskite films through rapid NIRA processing. This approach not only significantly reduces energy consumption during production, but also substantially shortens the manufacturing cycle, paving a new path toward the commercial-scale application of perovskite solar modules.

Conductive hydrogels have garnered widespread attention as a versatile class of flexible electronics. Despite considerable advancements, current methodologies struggle to reconcile the fundamental trade-off between high conductivity and effective absorption-dominated electromagnetic interference (EMI) shielding, as dictated by classical impedance matching theory. This study addresses these limitations by introducing a novel synthesis of aramid nanofiber/MXene-reinforced polyelectrolyte hydrogels. Leveraging the unique properties of polyelectrolytes, this innovative approach enhances ionic conductivity and exploits the hydration effect of hydrophilic polar groups to induce the formation of intermediate water. This critical innovation facilitates polarization relaxation and rearrangement in response to electromagnetic fields, thereby significantly enhancing the EMI shielding effectiveness of hydrogels. The electromagnetic wave attenuation capacity of these hydrogels was thoroughly evaluated across both X-band and terahertz band frequencies, with further investigation into the impact of varying water content states—hydrated, dried, and frozen—on their electromagnetic properties. Moreover, the hydrogels exhibited promising capabilities beyond mere EMI shielding; they also served effectively as strain sensors for monitoring human motions, indicating their potential applicability in wearable electronics. This work provides a new approach to designing multifunctional hydrogels, advancing the integration of flexible, multifunctional materials in modern electronics, with potential applications in both EMI shielding and wearable technology.